Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented method comprising: receiving a request for a playlist of songs to be streamed to a streaming client device of a first user; providing streaming media comprising the playlist of songs to the streaming client device of the first user, the streaming media having primary content; receiving first reaction data derived from the streaming client device; determining whether the streaming client device satisfies a sharing criterion, wherein the sharing criterion describes the manner of output: responsive to determining that the streaming client device satisfies the sharing criterion, detecting additional client devices that are co-located with the streaming client device based on the additional client devices being within range of a short range wireless communications transceiver of the streaming client device, the additional client devices being other than the streaming client device; receiving additional reaction data derived from the additional client devices; determining, based on the first reaction data of the streaming client device and the additional reaction data of the additional client devices, that the first user and users of the additional client devices are consuming the same streamed media comprising the playlist of songs requested by the first user provided to the streaming client device; determining audience characteristics based on information associated with the first user and information associated with the users of the additional client devices; and selecting additional content to be streamed, the additional content interspersed with the primary content, the selection based on the determined audience characteristics.
A system for dynamically enhancing streaming media playlists based on real-time audience reactions and co-located device detection. The invention addresses the challenge of personalizing content for groups of users consuming the same media stream, rather than just individual listeners. It involves a streaming platform that receives a request for a song playlist from a primary user's device, streams the media to that device, and captures reaction data (e.g., likes, skips, or dwell time) from the user's interaction with the content. If the primary device meets a predefined sharing criterion (e.g., proximity-based sharing enabled), the system detects nearby co-located devices within range of a short-range wireless transceiver (such as Bluetooth or Wi-Fi Direct). Reaction data from these additional devices is then collected. The system analyzes both the primary user's and co-located users' reactions to determine if they are consuming the same streamed playlist. Using profile data (e.g., demographics, listening history, or social connections) associated with all users in the detected group, the system infers audience characteristics. Based on these inferred characteristics, the system selects and inserts supplementary content (e.g., targeted ads, related tracks, or contextual media) into the ongoing stream. This additional content is tailored to the collective preferences or attributes of the group, enhancing engagement or monetization opportunities. The goal is to transform passive individual listening into a more interactive, socially informed streaming experience that adapts in real time to the actual audience present.
2. The computer-implemented method of claim 1 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: correlating the first reaction data and the additional reaction data with known information about the streamed primary content, the first reaction data and the additional reaction data comprising movement data collected by sensors of the streaming client device and by sensors of the additional client devices.
The invention relates to a computer-implemented system for detecting shared media consumption among multiple users by analyzing sensor data from their devices. The core problem addressed is identifying when different users are simultaneously experiencing the same media content, such as a video or audio stream, without relying solely on explicit user input. The method involves collecting movement data from sensors embedded in client devices, such as smartphones, tablets, or computers, while users are streaming primary content. This movement data includes motion patterns, device orientation, or other sensor readings that may correlate with user engagement or reaction to the media. The system then compares this reaction data from multiple users with known information about the streamed content, such as timestamps, scene changes, or audio cues, to determine if they are consuming the same media at the same time. By correlating sensor-derived reaction data with content metadata, the invention enables automatic detection of shared media consumption without requiring users to manually indicate their activity. This approach leverages passive data collection to infer engagement, making it useful for applications like social media synchronization, content recommendation, or audience analytics. The system operates in real-time or near-real-time, processing sensor inputs to dynamically identify synchronized media consumption across distributed devices.
3. The computer-implemented method of claim 2 , wherein the known information about the streamed primary content comprises timing of changes in volume or timing of changes in pitch of audio within the streamed primary content.
A computer-implemented method for identifying secondary content in a streamed primary content by analyzing audio characteristics. The method detects secondary content such as advertisements or promotional segments by monitoring changes in audio volume or pitch within the primary content stream. By identifying timing patterns in these audio variations, the system can distinguish between the main program and inserted secondary content without relying on metadata or external cues. This approach enables real-time or near-real-time detection of secondary content in live or pre-recorded media streams, improving content segmentation and user experience. The technique leverages audio signal processing to analyze temporal changes in volume or pitch, which serve as indicators of content transitions or embedded secondary material. This method is particularly useful in environments where metadata is unavailable or unreliable, such as over-the-air broadcasts or unencrypted streaming services. The system can be implemented as part of a media processing pipeline, where audio analysis is performed alongside or in place of traditional content identification methods.
4. The computer-implemented method of claim 3 , wherein determining that the first user and the users of the additional client devices are consuming the same media further comprises: determining that particular reactions identified within the first reaction data and within the additional reaction data occurred within a threshold time of the changes in volume or pitch of the streamed primary content.
The invention relates to a computer-implemented system for synchronizing user interactions with media content across multiple client devices. The core problem addressed is enabling real-time or near-real-time coordination of user reactions—such as emotional responses or engagement metrics—with dynamic changes in the media stream, such as volume or pitch variations. This is achieved by analyzing reaction data from a first user and additional users on separate devices, then identifying whether specific reactions occurred within a defined time window of detected changes in the media's audio characteristics. The method involves capturing reaction data (e.g., facial expressions, biometric signals, or explicit inputs) from multiple users consuming the same media stream, processing this data to detect reactions, and comparing their timing against detected audio fluctuations in the content. By establishing a temporal correlation between user reactions and media changes, the system enables synchronized experiences, such as shared viewing sessions, interactive content adjustments, or aggregated feedback analysis. The threshold time window ensures precision in matching reactions to relevant media events, distinguishing meaningful interactions from random or unrelated responses. This approach enhances collaborative media consumption, personalized content delivery, and real-time audience engagement analytics.
5. The computer-implemented method of claim 1 , wherein determining audience characteristics based on information associated with the first user and information associated with the users of the additional client devices comprises accessing user profiles associated with the users of the additional client devices.
This invention relates to computer-implemented methods for analyzing audience characteristics in a networked environment. The problem addressed is the need to accurately determine the demographics, preferences, or behaviors of users in a shared digital space, such as a social media platform, online forum, or collaborative application, to improve content delivery, advertising, or user engagement. The method involves collecting and analyzing information associated with multiple users to assess audience characteristics. Specifically, it accesses user profiles linked to the users of additional client devices participating in the same digital interaction. These profiles may contain data such as age, location, browsing history, or interaction patterns. By aggregating and processing this information, the system can derive insights about the collective audience, such as dominant age groups, geographic distributions, or shared interests. This enables personalized content recommendations, targeted advertising, or dynamic adjustments to the user experience based on real-time audience analysis. The method may also involve integrating additional data sources, such as device metadata or historical interaction logs, to refine the audience characterization. The goal is to provide a more accurate and context-aware understanding of the audience, enhancing the relevance and effectiveness of digital interactions. This approach is particularly useful in environments where user engagement is critical, such as live streaming, collaborative editing, or social media platforms.
6. The computer-implemented method of claim 1 , wherein the first device receives the streaming media via an application and each of the other devices includes a corresponding application.
This invention relates to a system for synchronizing streaming media playback across multiple devices. The problem addressed is the lack of seamless synchronization when multiple users watch or listen to the same media content on different devices, leading to playback delays, desynchronization, or interruptions. The solution involves a method where a first device receives streaming media via an application, and each of the other devices in the system also runs a corresponding application. The applications on the devices communicate to ensure synchronized playback, allowing users to experience the media simultaneously without delays or mismatches. The method may include techniques for compensating for network latency, adjusting playback timing, or coordinating user interactions across devices. The applications may also support features like shared playback controls, real-time annotations, or collaborative viewing experiences. The system is designed to work with various types of streaming media, including video, audio, or interactive content, and can be implemented on different device types, such as smartphones, tablets, smart TVs, or computers. The synchronization process may involve exchanging timing signals, buffering adjustments, or dynamic latency compensation to maintain alignment. The invention aims to enhance collaborative media consumption by ensuring all users experience the content in sync, regardless of network conditions or device capabilities.
7. The computer-implemented method of claim 1 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: determining a degree of similarity among the first reaction data comprising movement data collected by sensors of the streaming client device and the additional reaction data comprising movement data collected by sensors of the additional client devices.
The invention relates to a computer-implemented method for identifying shared media consumption among multiple users by analyzing sensor data from their client devices. The system detects when different users are consuming the same media content by comparing movement data collected from sensors on their streaming devices. This involves calculating a degree of similarity between the movement patterns of the first user and those of additional users. The method uses this similarity metric to determine whether the users are likely watching the same content, even if they are not explicitly linked or in the same location. By leveraging sensor data such as accelerometer or gyroscope readings, the system can infer shared media consumption without requiring direct user input or explicit synchronization. This approach enables applications such as social media features, collaborative recommendations, or synchronized viewing experiences based on real-time or historical movement data. The core technical contribution is the use of movement data as a proxy for media consumption alignment, providing a passive and unobtrusive way to detect shared viewing behavior.
8. A non-transitory computer-readable storage medium storing instructions that when executed by a computer processor perform actions comprising: receiving a request for a playlist of songs to be streamed to a streaming client device of a first user: providing streaming media comprising the playlist of songs to the streaming client device of the first user, the streaming media having primary content; receiving first reaction data derived from the streaming client device; determining whether the streaming client device satisfies a sharing criterion, wherein the sharing criterion describes the manner of output: responsive to determining that the streaming client device satisfies the sharing criterion, detecting additional client devices that are co-located with the streaming client device based on the additional client devices being within range of a short range wireless communications transceiver of the streaming client device, the additional client devices being other than the streaming client device; receiving additional reaction data derived from the additional client devices; determining, based on the first reaction data of the streaming client device and the additional reaction data of the additional client devices, that the first user and users of the additional client devices are consuming the same streamed media comprising the playlist of songs requested by the first user to the streaming client device; determining audience characteristics based on information associated with the first user and information associated with the users of the additional client devices; and selecting additional content to be streamed, the additional content interspersed with the primary content, the selection based on the determined audience characteristics.
This invention relates to a system for dynamically selecting and streaming media content to a group of co-located users based on their collective reactions and audience characteristics. The system receives a request for a playlist of songs from a first user's streaming client device and provides the requested playlist as primary content. While streaming, the system collects reaction data from the first user's device and checks if the device meets a sharing criterion, which determines how the content is output (e.g., via speakers or headphones). If the criterion is satisfied, the system detects nearby client devices using short-range wireless communication (e.g., Bluetooth or Wi-Fi) and collects reaction data from these additional devices. The system then determines if the first user and nearby users are consuming the same streamed playlist. Based on the combined reaction data and audience characteristics (e.g., user preferences, demographics, or behavior), the system selects additional content (e.g., advertisements, recommendations, or interstitials) to intersperse with the primary content. This approach enhances personalized content delivery by leveraging real-time feedback from a shared listening environment.
9. The non-transitory computer-readable storage medium of claim 8 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: correlating the first reaction data and the additional reaction data with known information about the streamed primary content, the first reaction data and the additional reaction data comprising movement data collected by sensors of the streaming client device and by sensors of the additional client devices.
This invention relates to a system for analyzing user reactions to streamed media content, such as videos or live broadcasts, to determine whether multiple users are consuming the same content simultaneously. The problem addressed is the difficulty in accurately identifying when different users are watching the same media, particularly in real-time, to enable features like synchronized reactions, shared experiences, or targeted advertising. The system collects reaction data from multiple client devices, including movement data from sensors like accelerometers or gyroscopes. This data is correlated with known information about the streamed content, such as timestamps, scene changes, or audio cues, to determine if the reactions align with the same media. For example, if multiple devices exhibit similar movement patterns at the same time, the system infers that the users are consuming the same content. The system can then use this information to synchronize reactions, enhance social features, or improve content recommendations. The approach improves upon traditional methods by leveraging sensor data for more accurate and real-time detection of shared media consumption.
10. The non-transitory computer-readable storage medium of claim 9 , wherein the known information about the streamed primary content comprises timing of changes in volume or timing of changes in pitch of audio within the streamed primary content.
This invention relates to analyzing streamed primary content, such as audio or video, to extract timing information about changes in volume or pitch within the audio portion. The system processes the streamed content to identify these changes and uses the extracted timing data to enhance content delivery, synchronization, or analysis. The method involves detecting variations in audio characteristics, such as volume fluctuations or pitch shifts, and recording the precise moments these changes occur. This timing information can be used for various applications, including content synchronization, adaptive streaming, or audio processing. The system may also compare the detected timing data against known patterns or reference points to improve accuracy or detect anomalies. The invention is particularly useful in scenarios where precise timing of audio changes is critical, such as in live broadcasts, multimedia synchronization, or automated content analysis. By leveraging this timing data, the system enables more efficient and accurate handling of streamed content, improving user experience and content processing workflows.
11. The non-transitory computer-readable storage medium of claim 10 , wherein determining that the first user and the users of the additional client devices are consuming the same media further comprises: determining that particular reactions identified within the first reaction data and within the additional reaction data occurred within a threshold time of the changes in volume or pitch of the streamed primary content.
This invention relates to a system for analyzing user reactions to media content in real-time, particularly focusing on synchronizing reactions across multiple users. The problem addressed is the difficulty in accurately determining whether users are experiencing the same media content simultaneously, especially when reactions may occur at slightly different times due to network delays or individual user behavior. The system involves a non-transitory computer-readable storage medium storing instructions that, when executed, perform a method for processing reaction data from multiple client devices. The method includes receiving reaction data from a first client device and additional client devices, where the reaction data includes timestamps and identifiers for reactions such as laughter, applause, or other responses to media content. The system analyzes changes in volume or pitch of the streamed primary content, such as audio or video, to identify key moments that likely trigger reactions. To confirm that users are consuming the same content, the system checks whether specific reactions from different users occurred within a threshold time window of these content changes. This ensures that reactions are correlated with the same media events, even if slight timing discrepancies exist. The method also involves comparing reaction patterns across users to further validate synchronization. This approach improves the accuracy of real-time media engagement analysis, enabling better content recommendations, audience insights, and interactive features.
12. The non-transitory computer-readable storage medium of claim 8 , wherein determining audience characteristics based on information associated with the first user and information associated with the users of the additional client devices comprises accessing user profiles associated with the users of the additional client devices.
This invention relates to a system for analyzing audience characteristics in a networked environment, particularly for optimizing content delivery or interaction based on user profiles. The system determines audience characteristics by accessing and analyzing user profiles associated with multiple client devices. These profiles contain information about the users, such as preferences, behavior, demographics, or historical interactions. By aggregating and processing this data, the system can identify patterns, trends, or commonalities among the users, enabling personalized or targeted content recommendations, advertisements, or system adjustments. The invention may be implemented in social media platforms, streaming services, or other digital environments where understanding audience behavior is valuable. The core technical challenge addressed is efficiently gathering and interpreting distributed user data to derive meaningful insights without compromising privacy or performance. The solution involves a non-transitory computer-readable storage medium storing executable instructions that, when executed, perform the audience analysis by cross-referencing user profiles from multiple devices. This approach enhances user engagement by tailoring experiences to the collective characteristics of the audience.
13. The non-transitory computer-readable storage medium of claim 8 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: determining a degree of similarity among the first reaction data comprising movement data collected by sensors of the streaming client device and the additional reaction data comprising movement data collected by sensors of the additional client devices.
This invention relates to a system for analyzing user reactions to media content, particularly in a shared viewing environment. The problem addressed is the need to accurately determine whether multiple users are simultaneously consuming the same media content, such as a video or audio stream, by analyzing their physical reactions. The system collects movement data from sensors on client devices, such as accelerometers or gyroscopes, to detect user reactions like head movements, gestures, or body shifts in response to the media. The system then compares the reaction data from a primary user with that of additional users to assess the degree of similarity. If the reactions align closely, it concludes that all users are consuming the same media. This allows for synchronized experiences, such as shared reactions, collaborative features, or targeted content delivery. The invention improves upon traditional methods by using sensor-based reaction data rather than relying solely on explicit user input or metadata, providing a more dynamic and accurate assessment of shared media consumption. The system may also adjust media playback or user interfaces based on the detected reactions, enhancing engagement and interactivity.
14. A computer system comprising: a computer processor; and a non-transitory computer-readable storage medium storing instructions that when executed by a computer processor perform actions comprising: receiving a request for a playlist of songs to be streamed to a streaming client device of a first user; providing streaming media comprising the playlist of songs to the streaming client device of the first user, the streaming media having primary content; receiving first reaction data derived from the streaming client device; determining whether the streaming client device satisfies a sharing criterion, wherein the sharing criterion describes the manner of output; responsive to determining that the streaming client device satisfies the sharing criterion, detecting additional client devices that are co-located with the streaming client device based on the additional client devices being within range of a short range wireless communications transceiver of the streaming client device, the additional client devices being other than the streaming client device; receiving additional reaction data derived from the additional client devices; determining, based on the first reaction data of the streaming client device and the additional reaction data of the additional client devices, that the first user and users of the additional client devices are consuming the same streamed media comprising the playlist of songs requested by the first user provided to the streaming client device; determining audience characteristics based on information associated with the first user and information associated with the users of the additional client devices; and selecting additional content to be streamed, the additional content interspersed with the primary content, the selection based on the determined audience characteristics.
This invention relates to a computer system for dynamically selecting and streaming media content based on real-time audience reactions and characteristics. The system addresses the challenge of personalizing media streams in shared listening environments where multiple users may be co-located but not necessarily synchronized in their content consumption. The system receives a request for a playlist of songs from a primary user's streaming client device and streams the media to that device. As the media plays, the system collects reaction data from the primary device, such as user interactions or feedback. If the primary device meets a predefined sharing criterion—such as being in a shared physical space—the system detects nearby client devices using short-range wireless communication (e.g., Bluetooth or Wi-Fi). It then gathers reaction data from these additional devices to confirm that the users are collectively consuming the same streamed playlist. The system analyzes the combined reaction data from all devices to determine audience characteristics, such as user preferences, demographics, or behavioral patterns. Based on this analysis, it selects supplementary content (e.g., advertisements, recommendations, or interstitial media) to intersperse with the primary playlist. This ensures the content is tailored to the collective audience, enhancing engagement and relevance in shared listening scenarios. The system dynamically adjusts content delivery without requiring explicit user input, improving the streaming experience for groups.
15. The computer-system of claim 14 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: correlating the first reaction data and the additional reaction data with known information about the streamed primary content, the first reaction data and the additional reaction data comprising movement data collected by sensors of the streaming client device and by sensors of the additional client devices.
This invention relates to a computer system for analyzing user reactions to streamed media content. The system addresses the challenge of determining whether multiple users are consuming the same media content by correlating their reactions with known information about the content. The system includes a streaming client device and additional client devices, each equipped with sensors to collect reaction data, such as movement data, from users. The system processes this reaction data to identify patterns that indicate users are experiencing the same media content. By comparing the reaction data from different devices with known characteristics of the streamed content, the system can determine whether the users are consuming the same media. This allows for synchronized or coordinated experiences, such as shared reactions or collaborative interactions, based on the analysis of user movements and other sensor-collected data. The system enhances media consumption by enabling real-time synchronization and shared experiences among users.
16. The computer system of claim 15 , wherein the known information about the streamed primary content comprises timing of changes in volume or timing of changes in pitch of audio within the streamed primary content.
This invention relates to a computer system for analyzing and processing streamed primary content, such as audio or video, to detect and utilize known information about the content. The system addresses the problem of efficiently identifying and leveraging specific characteristics within streamed media, such as timing patterns in audio volume or pitch changes, to enhance content processing, synchronization, or user interaction. The computer system includes a processor and memory storing instructions that, when executed, cause the system to receive streamed primary content and analyze it to extract known information. This known information includes timing data related to changes in audio volume or pitch within the content. The system may also process secondary content, such as advertisements or metadata, and synchronize or integrate it with the primary content based on the extracted timing information. For example, the system can align secondary content with specific volume or pitch changes in the primary content to ensure seamless transitions or targeted delivery. Additionally, the system may generate or modify output signals based on the analyzed content, such as adjusting playback parameters or triggering actions in response to detected timing patterns. The invention improves content delivery by enabling precise synchronization and dynamic adjustments, enhancing user experience and content relevance. The system is particularly useful in applications requiring real-time analysis and adaptation of streamed media, such as live broadcasts, interactive content, or automated content insertion.
17. The computer system of claim 16 , wherein determining that the first user and the users of the additional client devices are consuming the same media further comprises: determining that particular reactions identified within the first reaction data and within the additional reaction data occurred within a threshold time of the changes in volume or pitch of the streamed primary content.
The invention relates to a computer system for analyzing and synchronizing user reactions to media content across multiple client devices. The system detects and processes reaction data from users consuming the same media, such as audio or video content, to identify patterns and correlations in their responses. The system determines that users are consuming the same media by analyzing reaction data, which includes user inputs like clapping, cheering, or other audible or visual responses, and comparing these reactions to changes in the media content, such as volume or pitch variations. Specifically, the system checks whether particular reactions from different users occurred within a short time window of these content changes, ensuring that the reactions are synchronized and likely triggered by the same media events. This helps identify shared experiences among users and can be used for applications like live event engagement analysis, social media synchronization, or content recommendation systems. The system enhances media consumption by providing insights into how groups of users react to content in real time, improving interactivity and personalization.
18. The computer system of claim 14 , wherein determining that the first user and the users of the additional client devices are consuming the same media comprises: determining a degree of similarity among the first reaction data comprising movement data collected by sensors of the streaming client device and the additional reaction data comprising movement data collected by sensors of the additional client devices.
This invention relates to a computer system that analyzes user reactions to media content in real-time to determine shared experiences among multiple users. The system collects reaction data, including movement data from sensors on client devices, to assess how users are engaging with the same media. The system compares the reaction data from a first user's device with reaction data from additional client devices to determine if the users are consuming the same media. The comparison involves calculating a degree of similarity between the movement data from the first user's device and the movement data from the additional devices. If the similarity exceeds a threshold, the system concludes that the users are experiencing the same media content simultaneously. This allows the system to identify and group users who are reacting similarly to the same media, enabling features like synchronized interactions or shared experiences. The system may also adjust media playback or recommendations based on the detected shared reactions. The invention improves media engagement by dynamically detecting and responding to collective user behavior in real-time.
Unknown
December 29, 2020
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